AIMC Topic: Adult

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An exploratory study on predicting HER2-positive expression status of breast cancer using ultrasound radiomics combined with machine learning models.

PloS one
OBJECTIVE: This study aimed to investigate the feasibility and potential value of predictive models for human epidermal growth factor receptor 2 (HER2)-positive status in breast cancer (BC) based on radiomics features from conventional ultrasound ima...

Personalized real-time inference of momentary excitability from human EEG.

NeuroImage
The efficacy of transcranial magnetic stimulation (TMS) is often limited by non-adaptive protocols that disregard instantaneous brain states, potentially constraining therapeutic outcomes. Current EEG-guided approaches are hindered by their reliance ...

Re-examining the association between region-specific pain recurrence and muscle force strategies in patients with patellofemoral pain via OpenSim and artificial intelligence: a prospective cohort study toward targeted rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: This study utilized artificial intelligence (AI)-based machine learning algorithms, alongside the shapley additive explanations (SHAP) framework, to identify lower-limb muscle force patterns associated with recurrent patellofemoral pain (...

Explainable AI for infection prevention and control: modeling CPE acquisition and patient outcomes in an Irish hospital with transformers.

BMC medical informatics and decision making
BACKGROUND: Carbapenemase-Producing Enterobacteriace (CPE) poses a critical concern for infection prevention and control in hospitals. However, predictive modeling of previously highlighted CPE-associated risks such as readmission, mortality, and ext...

Ischemic heart disease mortality due to fine particulate matter in Seoul between 2016 and 2020.

BMC public health
BACKGROUND: Ischemic heart disease (IHD) continues to rank among the leading global causes of mortality, consistently linked to long-term exposure to fine particulate matter (PM). Despite a declining trend in the annual average PM concentration in Se...

Differentiation of optic disc edema and pseudopapilledema with deep learning on near-infrared reflectance images.

BMC ophthalmology
BACKGROUND: This study aimed to develop an artificial intelligence-based deep learning (DL) algorithm using near-infrared reflectance (NIR) images to differentiate between optic disc edema and pseudopapilledema, and to evaluate the diagnostic perform...

Deep multi-instance learning model based on gadoxetic acid-enhanced MRI for predicting microvascular invasion of hepatocellular carcinoma: a multicenter, retrospective study.

BMC cancer
OBJECTIVE: Microvascular invasion (MVI) is of great significance for the individualized treatment of hepatocellular carcinoma (HCC) and preoperative noninvasive prediction of MVI is still an urgent clinical problem. To explore the effects of differen...

Generative artificial intelligence models outperform students on divergent and convergent thinking assessments.

Scientific reports
Generative artificial intelligence (GenAI) has garnered significant attention for its remarkable capabilities and is now widely used in many creative domains, sparking scientific interest in its creative capacities. While previous studies have assess...

Artificial intelligence driven intraocular lens power calculation in extreme axial myopia.

Scientific reports
Accurate intraocular lens (IOL) power calculation is critical in cataract surgery, especially in patients with extreme axial myopia where traditional formulas often yield inaccurate results. This study retrospectively evaluated the accuracy of two AI...